Skip to main content

A floatview output widget for JupyterLab + GlueViz Visualization with plotly

Project description

Floatview Stats

Latest Release
PyPI Downloads

Floatview

A floatview output widget for JupyterLab and a data explorer for glue/iplotly

Installation

If you use jupyterlab 2.X:

pip install floatview
jupyter labextension install @jupyter-widgets/jupyterlab-manager@2.0.0
jupyter labextension install jupyterlab-plotly@4.9.0
jupyter labextension install plotlywidget@4.9.0
jupyter labextension install jupyterlab-floatview@0.3.1

If you use jupyterlab 1.X:

pip install floatview==0.2.0
jupyter labextension install @jupyter-widgets/jupyterlab-manager@1.0.1
jupyter labextension install jupyterlab-datawidgets@6.2.0
jupyter labextension install jupyterlab-plotly@1.0.0
jupyter labextension install plotlywidget@1.0.0
jupyter labextension install jupyterlab-floatview@0.2.0

older versions:

pip install floatview==0.1.18
jupyter labextension install @jupyterlab/plotly-extension@0.18.2
jupyter labextension install plotlywidget@0.9.1
jupyter labextension install @jupyter-widgets/jupyterlab-manager@0.38.1
jupyter labextension install jupyterlab-floatview@0.1.11

Usage

The floatview widget is used as a context manager, just like ipywidgets' output widget.

from floatview import Floatview
from ipywidgets import IntSlider

sc = Floatview(title='Floatview Output', mode='tab-after', active=True)
sl = IntSlider(description='Some slider')
with sc:
    display(sl)

When a single output is displayed in a Floatview, it is allowed to occupy all of the vertical space available. If more content is displayed, the natural height is used instead.

The gluemanagerwidget is used as a data/visualization manager for a glue dataset.

from floatview import GlueManagerWidget
from pandas import read_csv

data = read_csv('your_data.csv', index_col=False, usecols=cols)
gmw = GlueManagerWidget(data, modal=True, label="Data")

floatview

Available Visualizations

#Histogram (supports 1 component)
view = gmw.gluemanager.newView(
    "histogram",
    ["PULocationID"],
    "Histogram"
)

histogram

#Scatter (supports 2-n components)
view = gmw.gluemanager.newView(
    "scatter",
    ["PULocationID", "DOLocationID"],
    "Scatter"
)
view = gmw.gluemanager.newView(
    "composed_scatter",
    ["trip_distance", "payment_type", 'passenger_count'],
    "Composed Scatter"
)

scatter

#ErrorBar (supports 2-n components)
view = gmw.gluemanager.newView(
    "errorbar",
    ["trip_distance", "total_amount"],
    "Error"
)
view = gmw.gluemanager.newView(
    "composed_errorbar",
    ["trip_distance", "payment_type", 'passenger_count'],
    "Composed Error"
)

error

#Polynomial Fitting 2-n degree (supports n components)
view = gmw.gluemanager.newView(
    "composed_polyfit_3d",
    ["trip_distance", "total_amount"],
    "Polyfit"
);

polyfit

#scatter 3D (supports 3 components)
view = gmw.gluemanager.newView(
    "scatter3D",
    ["trip_distance", "total_amount", "passenger_count"],
    "Scatter3D"
)

scatter3d

#Contours 2D (supports 2 components)
view = gmw.gluemanager.newView(
    "contour",
    ["trip_distance", "total_amount"],
    "Contour"
);

contour

#Table (supports n components)
view = gmw.gluemanager.newView(
    "table",
    ['passenger_count', 'trip_distance', 'total_amount', 'payment_type'],
    "Table"
);

table

#Parallel coordinatess (supports n components)
view = gmw.gluemanager.newView(
    "parallels",
    ['passenger_count', 'trip_distance', 'total_amount', 'payment_type'],
    "Parallels"
);

parallels

#Parallel categories (supports n components)
view = gmw.gluemanager.newView(
    "parallelscat",
    ['passenger_count', 'trip_distance', 'total_amount', 'payment_type'],
    "Parallels Categ"
 );

parallelscat

#Sankey (supports n components)
view = gmw.gluemanager.newView(
    "sankey",
    ['passenger_count', 'trip_distance', 'total_amount', 'payment_type'],
    "Sankey"
);

sankey

#Sunburst (supports n components)
view = gmw.gluemanager.newView(
    "sunburst",
    ['passenger_count', 'trip_distance', 'total_amount', 'payment_type'],
    "Sunburst"
);

sunburst

#Sankey Tree (supports n components)
view = gmw.gluemanager.newView(
    "sankeytree",
    ['total_amount', 'payment_type', 'passenger_count', ],
    "Sankey Tree"
);

sankeytree

#Scatter Matrix (supports n components)
view = gmw.gluemanager.newView(
    "scattermatrix",
    ['passenger_count', 'trip_distance', 'total_amount', 'payment_type'],
    "scatter Matrix"
);

scattermatrix

#Correlation Matrix (supports n components)
view = gmw.gluemanager.newView(
    "corrcoef",
    ['passenger_count', 'trip_distance', 'total_amount', 'payment_type'],
    "Correlation Matrix"
);

corrcoef

#Principal components (supports n components)
view = gmw.gluemanager.newView(
    "pca",
    ['passenger_count', 'trip_distance', 'total_amount', 'payment_type'],
    "Principal components"
);

pca

#Network (supports 2 components)
view = gmw.gluemanager.newView(
    "network",
    ['trip_distance', 'total_amount'],
    "Network"
);

network

#Image (supports 3 components)
view = gmw.gluemanager.newView(
    "image",
    ["trip_distance", "total_amount", 'passenger_count'],
    "Image"
);

image

#Lines (supports n components)
view = gmw.gluemanager.newView(
    "composed_lines",
    ["trip_distance", "payment_type", 'passenger_count'],
    "Lines"
);

lines

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

floatview-0.3.2-py2.py3-none-any.whl (23.2 MB view details)

Uploaded Python 2Python 3

File details

Details for the file floatview-0.3.2-py2.py3-none-any.whl.

File metadata

  • Download URL: floatview-0.3.2-py2.py3-none-any.whl
  • Upload date:
  • Size: 23.2 MB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.0 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

File hashes

Hashes for floatview-0.3.2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 e4d6504a7f24f6d7b02e2a4b02689f000c1e291839372a1adf8b94b198d98db3
MD5 50bfa1d45e2d938296af75dc3793f7a0
BLAKE2b-256 14018e4720988499da4b24d1ab54284761461e78f386dd94296103b5c975a79e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page